Selection bias in case-control studies using relatives as the controls

Investigators have suggested using relatives of cases as the control group when studying complex diseases thought to have a major genetic component. However, there is a concern about possible bias and we developed a model to examine the possibility of bias in the selection of relatives as the control group. Assuming the exposure-specific risks of disease remain constant over time, the results indicate that even when there is a correlation in the exposure status among relatives, selection of controls from relatives of cases does not, of itself, introduce bias in the estimate of effect.     

Selection of controls in injury case-control studies

PURPOSE: To assist in elucidating principles underlying the design of injury case-control studies.APPROACH: We begin by defining "event" as the sequence of circumstances that place a person at risk of injury (e.g. bicycle crash) and "injury given the event" as the resultant physical damage (e.g. head injury in bicycle crash). We then identify two broad classes of research question: 1) Studies of risk factors for the event, and, 2) Studies of risk factors for injury given the event. The study base for the first type of research question is all persons at risk of the event, while the study base for the second type is all persons who experience the event, and are therefore at risk of injury. It follows that in studies of risk factors for injury given the event, the controls should be a sample of all persons who experience the event. For example, in a study of bicycle helmets and head injuries, a suitable case group would be cyclists treated for head injury following a bicycle crash. The appropriate control group is drawn from the base population of all cyclists who crashed, including those who had no injuries. The control group may be restricted to cyclists who crashed and sought treatment for non-head injury under the assumption that the exposure distribution (prevalence of cycle helmet use) in the crash/no injury group is identical to the exposure distribution in the crash/non-head injury group.CONCLUSIONS: It is over ten years since innovative researchers in Seattle first applied the case-control design to the problem of bicycle crashes. Since then, successive bicycle injury studies at other centers have largely failed to extend and refine the Seattle methodology. A more critical approach to the design of case-control studies is required if we are to continue to advance the field of injury epidemiology.     

Reporting and selection bias in case-control studies of congenital malformations.

Retrospective studies of congenital malformations frequently rely on exposures reported by study subjects. Differential error in exposure reporting by cases and controls, which has alternatively been referred to as "recall bias" and "reporting bias," may result in a biased effect measure. Some authors have attempted to avoid reporting bias by comparing exposures between two malformed groups, rather than between cases and nonmalformed controls. This approach, however, may introduce its own bias, which we call selection bias. Both reporting bias and selection bias are shown to be algebraically equivalent to bias arising from exposure misclassification. The magnitudes of these biases are compared for a range of plausible parametric values. The case-control design is sensitive to both differential reporting and selection bias, and the choice of study design involves balancing these two sources of bias.     

Selection bias in the assessment of gene-environment interaction in case-control studies

Selection bias is a common concern in epidemiologic studies, particularly case-control studies. Selection bias in the odds ratio occurs when participation depends jointly on exposure and disease status. General results for understanding when selection bias may affect studies involving gene-environment interactions have not yet been developed. In this paper, the authors show that the assessment of gene-environment interactions will not be subject to selection bias under the assumption that genotype does not influence participation conditional on exposure and disease status. This is true even when selection, including self-selection of subjects, is jointly influenced by exposure and disease and regardless of whether the genotype is related to exposure, disease, or both. The authors present an example to illustrate this concept.     

Selection of controls in case-control studies. II. Types of controls.

Types of control groups are evaluated using the principles described in paper 1 of the series, "Selection of Controls in Case-Control Studies" (S. Wacholder et al. Am J Epidemiol 1992;135:1019-28). Advantages and disadvantages of population controls, neighborhood controls, hospital or registry controls, medical practice controls, friend controls, and relative controls are considered. Problems with the use of decreased controls and proxy respondents are discussed.     

Selection of controls in case-control studies. I. Principles.

A synthesis of classical and recent thinking on the issues involved in selecting controls for case-control studies is presented in this and two companion papers (S. Wacholder et al. Am J Epidemiol 1992;135:1029-50). In this paper, a theoretical framework for selecting controls in case-control studies is developed. Three principles of comparability are described: 1) study base, that all comparisons be made within the study base; 2) deconfounding, that comparisons of the effects of the levels of exposure on disease risk not be distorted by the effects of other factors; and 3) comparable accuracy, that any errors in measurement of exposure be nondifferential between cases and controls. These principles, if adhered to in a study, can reduce selection, confounding, and information bias, respectively. The principles, however, are constrained by an additional efficiency principle regarding resources and time. Most problems and controversies in control selection reflect trade-offs among these four principles.     

Selection bias in occupational case-control studies that use death registries to select subjects: a discussion and demonstration

Some epidemiologic studies have selected subjects from death registries. This method is, however, subject to substantial systematic bias that arises from the fact that different segments of society have different risks of death in any year. Different occupational groups will thus have unequal probabilities of entering the pool of potential controls, and biased estimates of the odds ratios that relate occupation to disease will result. Failure to recognize the bias may lead to invalid conclusions. This selection bias is discussed, with particular reference to studies of malignancies among farmers. The bias is demonstrated by using data from studies of Parkinson's disease and sinonasal cancer.     

Selection of controls in case-control studies. III. Design options.

Several design options available in the planning stage of case-control studies are examined. Topics covered include matching, control/case ratio, choice of nested case-control or case-cohort design, two-stage sampling, and other methods that can be used for control selection. The effect of potential problems in obtaining comparable accuracy of exposure is also examined. A discussion of the difficulty in meeting the principles of study base, deconfounding, and comparable accuracy (S. Wacholder et al. Am J Epidemiol 1992;135:1019-28) in a single study completes this series of papers.     

Ascertainment bias in family-based case-control studies

In a family-matched case-control study, a population-based sample of cases is selected from a well-defined geographic region over a fixed period of time. For diseases of adult onset, the control is generally a sibling or cousin who is matched on sex and age without regard to location of residence. Such a design can lead to biased estimates of environmental relative risk if the prevalence of an environmental risk factor varies by the geographic region from which the cases and controls are drawn. However, assuming the independence of genotype and environmental exposure, the estimators for the gene and gene-environment interaction effects are consistent. This suggests that we must use caution in interpreting parameters that estimate environmental main effects from a family-based case-control study if controls are selected from outside the case-ascertainment region.     

Cancer case-control studies with other cancers as controls

Theoretical considerations concerning the use of other cancer patients as controls in cancer case-control studies are reviewed. Selection bias may be a problem in that some other cancers may be caused by the exposure under study biasing the odds ratio towards unity. Such bias is noted to be greatest with low prevalence exposures associated with high attributable risks for other cancers. However, it may be possible to identify selection bias with other cancer controls using census or other general population data. In addition, using other cancers as controls has important advantages with regard to recall and interviewer bias, which may be of unknown magnitude and direction when using general population controls. A further disadvantage of general population controls is that separate selection of decreased controls should usually be made for deceased cases, whereas a mixture of live and deceased controls can be expected when selecting other cancer patients as controls. Since there are also logistical and cost advantages in using other cancer patients as controls, this study design is likely to be used increasingly in the future, particularly in cancer registry settings.     

Problems in the use of dead controls in case-control studies. I. General results

A recently completed case-control study in the Minneapolis-St. Paul area using population-based living controls and dead controls afforded the opportunity to compare these two control groups on their exposure histories. Detailed information was obtained by interview from 697 living controls and the next of kin of 493 dead controls. The dead controls of both sexes were reported to have been significantly heavier cigarette smokers compared with living controls, as well as heavier consumers of hard liquor, beer, and drugs, and to have had more adulthood diseases. There were no consistent differences between the control groups for consumption of nonalcoholic beverages, some aspects of diet, ethnic and religious background, usual occupation, and residential history. It appears that exposures associated with premature death are overrepresented in dead controls compared with living controls, while those variables not associated with premature mortality are distributed more or less similarly between the two groups.     

Selection bias due to differential participation in a case-control study of mobile phone use and brain tumors

PURPOSE: To evaluate the possible selection bias related to the differential participation of mobile phone users and non-users in a Finnish case-control study on mobile phone use and brain tumors. METHODS: Mobile phone use was investigated among 777 controls and 726 cases participating in the full personal interview (full participants), and 321 controls and 103 cases giving only a brief phone interview (incomplete participants). To assess selection bias, the Mantel-Haenszel estimate of odds ratio was calculated for three different groups: full study participants, incomplete participants, and a combined group consisting of both full and incomplete participants. RESULTS: Among controls, 83% of the full participants and 73% of the incomplete participants had regularly used a mobile phone. Among cases, the figures were 76% and 64%, respectively. The odds ratio for brain tumor based on the combined group of full and incomplete participants was slightly closer to unity than that based only on the full participants. CONCLUSIONS: Selection bias tends to distort the effect estimates below unity, while analyses based on more comprehensive material gave results close to unity.